Figure 2

Variant prioritization. The variant prioritization step will annotate input variants and then score them using the weighted scoring scheme. Features used in the weighted scoring scheme can be classified into `functional annotations’, `conservation’, `nucleotide-level analysis’, `network analysis’, and `recurrence’. `Recurrence’ feature could be detected from user-input cancer samples and also from `Recurrence DB’ (* means optional. User can choose to use the `Recurrence DB’ or not). Different from other features, `recurrence’ depends on the user-input (for example, if user only uploads one sample and chooses not to use the `Recurrence DB’, then `recurrence’ feature will not be observed for any variant). Each feature is assigned a weighted score (Material and methods). Scores obtained from the top grey panel are called `core scores’, which is independent of the user’s choice (see above for `recurrence’ feature). Variants with the `recurrence’ feature are assigned an additional score in the final output. In addition to features used in the scoring scheme, other features are used to highlight potentially interesting variants, such as variants associated with known cancer genes.